



"""simple docstring"""







import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
			import PIL.Image

			from .features import FeatureType


UpperCamelCase     =							None
UpperCamelCase     =							"""<""" if sys.byteorder == """little""" else """>"""
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
UpperCamelCase     =							[
    np.dtype("""|b1"""),
    np.dtype("""|u1"""),
    np.dtype("""<u2"""),
    np.dtype(""">u2"""),
    np.dtype("""<i2"""),
    np.dtype(""">i2"""),
    np.dtype("""<u4"""),
    np.dtype(""">u4"""),
    np.dtype("""<i4"""),
    np.dtype(""">i4"""),
    np.dtype("""<f4"""),
    np.dtype(""">f4"""),
    np.dtype("""<f8"""),
    np.dtype(""">f8"""),
]






@dataclass
class       UpperCamelCase__			:

			"""simple docstring"""


			A__	:					bool							  =     True
			A__	:					Optional[str]							  =     None
			# Automatically constructed
			A__	:					ClassVar[str]							  =     "PIL.Image.Image"
			A__	:					ClassVar[Any]							  =     pa.struct({"bytes": pa.binary(), "path": pa.string()}      )
			A__	:					str							  =     field(default="Image"       ,		init=_lowerCAmelCase       ,		repr=_lowerCAmelCase      )


			def __call__(      self		)      ->	str:
				return self.pa_type


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	dict:
				if config.PIL_AVAILABLE:
					import PIL.Image
				else:
					raise ImportError("To support encoding images, please install 'Pillow'."		)

				if isinstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		):
					A__											=					np.array(SCREAMING_SNAKE_CASE__		)

				if isinstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		):
					return {"path": value, "bytes": None}
				elif isinstance(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__		):
					return {"path": None, "bytes": value}
				elif isinstance(SCREAMING_SNAKE_CASE__						,	np.ndarray		):
					# convert the image array to PNG/TIFF bytes
					return encode_np_array(SCREAMING_SNAKE_CASE__		)
				elif isinstance(SCREAMING_SNAKE_CASE__						,	PIL.Image.Image		):
					# convert the PIL image to bytes (default format is PNG/TIFF)
					return encode_pil_image(SCREAMING_SNAKE_CASE__		)
				elif value.get("path"		) is not None and os.path.isfile(value["path"]		):
					# we set "bytes": None to not duplicate the data if they're already available locally
					return {"bytes": None, "path": value.get("path"		)}
				elif value.get("bytes"		) is not None or value.get("path"		) is not None:
					# store the image bytes, and path is used to infer the image format using the file extension
					return {"bytes": value.get("bytes"		), "path": value.get("path"		)}
				else:
					raise ValueError(
					    f"""An image sample should have one of 'path' or 'bytes' but they are missing or None in {value}."""		)


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__=None		)      ->	"PIL.Image.Image":
				if not self.decode:
					raise RuntimeError("Decoding is disabled for this feature. Please use Image(decode=True) instead."		)

				if config.PIL_AVAILABLE:
					import PIL.Image
				else:
					raise ImportError("To support decoding images, please install 'Pillow'."		)

				if token_per_repo_id is None:
					A__											=					{}

				A__							,							A__											=					value["path"], value["bytes"]
				if bytes_ is None:
					if path is None:
						raise ValueError(f"""An image should have one of 'path' or 'bytes' but both are None in {value}."""		)
					else:
						if is_local_path(SCREAMING_SNAKE_CASE__		):
							A__											=					PIL.Image.open(SCREAMING_SNAKE_CASE__		)
						else:
							A__											=					path.split("::"		)[-1]
							try:
								A__											=					string_to_dict(SCREAMING_SNAKE_CASE__						,	config.HUB_DATASETS_URL		)["repo_id"]
								A__											=					token_per_repo_id.get(SCREAMING_SNAKE_CASE__		)
							except ValueError:
								A__											=					None
							with xopen(SCREAMING_SNAKE_CASE__						,	"rb"						,	use_auth_token=SCREAMING_SNAKE_CASE__		) as f:
								A__											=					BytesIO(f.read()		)
							A__											=					PIL.Image.open(bytes_		)
				else:
					A__											=					PIL.Image.open(BytesIO(bytes_		)		)
				image.load()  # to avoid "Too many open files" errors
				return image


			def   snake_case__	(      self		)      ->	Union["FeatureType", Dict[str, "FeatureType"]]:
				from .features import Value

				return (
				    self
				    if self.decode
				    else {
				        "bytes": Value("binary"		),
				        "path": Value("string"		),
				    }
				)


			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	pa.StructArray:
				if pa.types.is_string(storage.type		):
					A__											=					pa.array([None] * len(SCREAMING_SNAKE_CASE__		)						,	type=pa.binary()		)
					A__											=					pa.StructArray.from_arrays([bytes_array, storage]						,	["bytes", "path"]						,	mask=storage.is_null()		)
				elif pa.types.is_binary(storage.type		):
					A__											=					pa.array([None] * len(SCREAMING_SNAKE_CASE__		)						,	type=pa.string()		)
					A__											=					pa.StructArray.from_arrays([storage, path_array]						,	["bytes", "path"]						,	mask=storage.is_null()		)
				elif pa.types.is_struct(storage.type		):
					if storage.type.get_field_index("bytes"		) >= 0:
						A__											=					storage.field("bytes"		)
					else:
						A__											=					pa.array([None] * len(SCREAMING_SNAKE_CASE__		)						,	type=pa.binary()		)
					if storage.type.get_field_index("path"		) >= 0:
						A__											=					storage.field("path"		)
					else:
						A__											=					pa.array([None] * len(SCREAMING_SNAKE_CASE__		)						,	type=pa.string()		)
					A__											=					pa.StructArray.from_arrays([bytes_array, path_array]						,	["bytes", "path"]						,	mask=storage.is_null()		)
				elif pa.types.is_list(storage.type		):
					A__											=					pa.array(
					    [encode_np_array(np.array(SCREAMING_SNAKE_CASE__		)		)["bytes"] if arr is not None else None for arr in storage.to_pylist()]						,	type=pa.binary()						,	)
					A__											=					pa.array([None] * len(SCREAMING_SNAKE_CASE__		)						,	type=pa.string()		)
					A__											=					pa.StructArray.from_arrays(
					    [bytes_array, path_array]						,	["bytes", "path"]						,	mask=bytes_array.is_null()		)
				return array_cast(SCREAMING_SNAKE_CASE__						,	self.pa_type		)







			def   snake_case__	(      self						,	SCREAMING_SNAKE_CASE__		)      ->	pa.StructArray:

				@no_op_if_value_is_null
				def path_to_bytes(SCREAMING_SNAKE_CASE__		):
					with xopen(SCREAMING_SNAKE_CASE__						,	"rb"		) as f:
						A__											=					f.read()
					return bytes_

				A__											=					pa.array(
				    [
				        (path_to_bytes(x["path"]		) if x["bytes"] is None else x["bytes"]) if x is not None else None
				        for x in storage.to_pylist()
				    ]						,	type=pa.binary()						,	)
				A__											=					pa.array(
				    [os.path.basename(SCREAMING_SNAKE_CASE__		) if path is not None else None for path in storage.field("path"		).to_pylist()]						,	type=pa.string()						,	)
				A__											=					pa.StructArray.from_arrays([bytes_array, path_array]						,	["bytes", "path"]						,	mask=bytes_array.is_null()		)
				return array_cast(SCREAMING_SNAKE_CASE__						,	self.pa_type		)



def       _lowerCamelCase				(							)	-> List[str]:






	"""simple docstring"""





	if config.PIL_AVAILABLE:
		import PIL.Image
	else:
		raise ImportError("To support encoding images, please install 'Pillow'."     )

	global _IMAGE_COMPRESSION_FORMATS
	if _IMAGE_COMPRESSION_FORMATS is None:
		PIL.Image.init()
		A__											=					list(set(PIL.Image.OPEN.keys()     ) & set(PIL.Image.SAVE.keys()     )     )
	return _IMAGE_COMPRESSION_FORMATS

def       _lowerCamelCase				(							UpperCAmelCase_ :       "PIL.Image.Image"     )	-> bytes:






	"""simple docstring"""





	A__											=					BytesIO()
	if image.format in list_image_compression_formats():
		A__											=					image.format
	else:
		A__											=					"PNG" if image.mode in ["1", "L", "LA", "RGB", "RGBA"] else "TIFF"
	image.save(UpperCAmelCase_,	format=UpperCAmelCase_     )
	return buffer.getvalue()

def       _lowerCamelCase				(							UpperCAmelCase_ :       "PIL.Image.Image"     )	-> dict:






	"""simple docstring"""





	if hasattr(UpperCAmelCase_,	"filename"     ) and image.filename != "":
		return {"path": image.filename, "bytes": None}
	else:
		return {"path": None, "bytes": image_to_bytes(UpperCAmelCase_     )}

def       _lowerCamelCase				(							UpperCAmelCase_ :       np.ndarray     )	-> dict:






	"""simple docstring"""





	if config.PIL_AVAILABLE:
		import PIL.Image
	else:
		raise ImportError("To support encoding images, please install 'Pillow'."     )

	A__											=					array.dtype
	A__											=					dtype.byteorder if dtype.byteorder != "=" else _NATIVE_BYTEORDER
	A__											=					dtype.kind
	A__											=					dtype.itemsize

	A__											=					None

	# Multi-channel array case (only np.dtype("|u1") is allowed)
	if array.shape[2:]:
		A__											=					np.dtype("|u1"     )
		if dtype_kind not in ["u", "i"]:
			raise TypeError(
			    F"""Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays."""     )
		if dtype is not dest_dtype:
			warnings.warn(F"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"""     )
    # Exact match
	elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
		A__											=					dtype
	else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
		while dtype_itemsize >= 1:
			A__											=					dtype_byteorder + dtype_kind + str(UpperCAmelCase_     )
			A__											=					np.dtype(UpperCAmelCase_     )
			if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
				warnings.warn(F"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"""     )
				break
			else:
				dtype_itemsize //= 2

	if dest_dtype is None:
		raise TypeError(
		    F"""Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}"""     )
	A__											=					PIL.Image.fromarray(array.astype(UpperCAmelCase_     )     )
	return {"path": None, "bytes": image_to_bytes(UpperCAmelCase_     )}




def       _lowerCamelCase				(							UpperCAmelCase_ :       Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]     )	-> List[dict]:






	"""simple docstring"""





	if config.PIL_AVAILABLE:
		import PIL.Image
	else:
		raise ImportError("To support encoding images, please install 'Pillow'."     )

	if objs:
		A__							,							A__											=					first_non_null_value(UpperCAmelCase_     )
		if isinstance(UpperCAmelCase_,	UpperCAmelCase_     ):
			return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
		if isinstance(UpperCAmelCase_,	np.ndarray     ):
			A__											=					no_op_if_value_is_null(UpperCAmelCase_     )
			return [obj_to_image_dict_func(UpperCAmelCase_     ) for obj in objs]
		elif isinstance(UpperCAmelCase_,	PIL.Image.Image     ):
			A__											=					no_op_if_value_is_null(UpperCAmelCase_     )
			return [obj_to_image_dict_func(UpperCAmelCase_     ) for obj in objs]
		else:
			return objs
	else:
		return objs








from unittest.mock import Mock, patch

from file_transfer.send_file import send_file
@patch("socket.socket"	)
@patch("builtins.open"	)
def 							UpperCamelCase_(					_A :Tuple					,  _A :str	)->		int:
			# ===== initialization =====
			UpperCamelCase__       =							Mock()
			UpperCamelCase__       =							conn, Mock()
			UpperCamelCase__       =							iter([1, None]	)
			UpperCamelCase__       =							lambda _A	: next(_A	)

			# ===== invoke =====
			send_file(filename="mytext.txt"					,  testing=_A	)

			# ===== ensurance =====
			sock.assert_called_once()
			sock.return_value.bind.assert_called_once()
			sock.return_value.listen.assert_called_once()
			sock.return_value.accept.assert_called_once()
			conn.recv.assert_called_once()

			file.return_value.__enter__.assert_called_once()
			file.return_value.__enter__.return_value.read.assert_called()

			conn.send.assert_called_once()
			conn.close.assert_called_once()
			sock.return_value.shutdown.assert_called_once()
			sock.return_value.close.assert_called_once()


